Generative AI Engineer — Healthcare & Government

Magpie Health Analytics, Inc.; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Magpie Health Analytics, Inc. is seeking an experienced AI Engineer to design, build, and operate secure, trustworthy generative AI solutions for healthcare clients.

You will enable fast access to authoritative program guidance by grounding LLMs in source docs and building robust ingestion pipelines. You will collaborate with PMs, data engineers, full stack developers, analysts, and stakeholders to deliver an AI-enabled decision-support capability with traceable sources, guardrails, and strong

Qualifications

• 5+ years of experience developing software and cloud-based solutions, with demonstrated recent experience designing and deploying LLM or generative AI applications.
• Strong proficiency in Python and experience with modern LLM APIs, SDKs, orchestration frameworks, and AI/ML libraries (e.g., Hugging Face, LangChain, LlamaIndex, or equivalent).
• Hands-on experience designing and deploying generative AI solutions, including embeddings, vector databases, and hybrid/semantic search.
• Experience with AWS AI and data services such as Amazon Bedrock, Amazon OpenSearch, Amazon Kendra, SageMaker, Lambda, or S3.
• Experience with prompt and context engineering, LLM evaluation, and techniques for reducing hallucinations and ensuring answers are grounded in source material.
• Designing AI applications to support multiple foundation models/providers and evaluating models based on accuracy, latency, cost, security, and use-case requirements.
• Experience with Agile software development methodologies.
• Experience with building and maintaining CI/CD pipelines, testing, and deploying infrastructure using services such as GitHub Actions, CloudFormation, Terraform, and/or Jenkins.
• Excellent problem-solving and communication skills, including the ability to explain AI capabilities and limitations to non-technical stakeholders.
• Ability to work independently and in a team, with strong attention to detail and presentation.

Responsibilities

• Design, develop, and maintain generative AI solutions that ground large language model (LLM) responses in authoritative source documentation.
• Build and maintain document ingestion pipelines, including parsing, chunking, metadata tagging, embedding generation, and vector/semantic search indexing.
• Collaborate with cross-functional teams and subject matter experts to understand user needs and translate them into requirements, prompts, and evaluation criteria.
• Implement responses with source citations and direct links to the underlying documentation to ensure traceability.
• Design and implement guardrails, including content filtering, scope restrictions, PII/PHI protections, and refusal handling for out-of-scope questions.
• Develop evaluation frameworks and test sets to measure retrieval quality, answer accuracy, groundedness, and consistency; monitor and tune performance over time.
• Deploy and operate solutions within approved AWS services and federal security controls, supporting documentation needed for security authorization and AI governance reviews.
• Implement logging, monitoring, and audit trails to support transparency, cost management, and responsible AI oversight.
• Write clean, reusable, and well-documented code, and participate in code reviews, testing, and deployment processes.
• Stay up to date with emerging AI technologies, models, and federal AI guidance.

Skills

Python

LLM APIs

Hugging Face

LangChain

LlamaIndex

AI/ML libraries

Agile methodologies

CI/CD

AWS services

Education

Master's degree in computer science, data science, engineering

Tools

GitHub Actions

Terraform

CloudFormation

Jenkins

SageMaker

Bedrock

OpenSearch

Kendra

Lambda

S3

Job description

Magpie Health Analytics, Inc. is seeking an experienced AI Engineer to design, build, and operate secure, trustworthy generative AI solutions for healthcare clients.

You will enable fast access to authoritative program guidance by grounding LLMs in source docs and building robust ingestion pipelines. You will collaborate with PMs, data engineers, full stack developers, analysts, and stakeholders to deliver an AI-enabled decision-support capability with traceable sources, guardrails, and strong